Introduction to data visualization
MACS 40700
University of Chicago
March 27, 2017
Course objectives
- Understand how the human mind perceives and interprets visual data
- Distinguish different types of visualizations and identify appropriate use cases
- Evaluate visualizations’ interpretability based on experimental design
- Apply data visualization methods using a reproducible workflow
Purpose of visualizations
- Any kind of visual representation of information designed to enable communication, analysis, discovery, exploration, etc.
- What to communicate
- How to communicate
Statistical graphics
- Visualize abstract data of a quantitative form
- Goals
Scatterplot matricies

Double-time bar charts

Double-time bar charts

Fitbit

Infographics
- Eye-catching
- Quickly convey information
- Not always accurate
Dr. John Snow

Charles Minard

Minard’s map of Napoleon’s march on Russia

NYTimes weather summaries
How Much Warmer Was Your City in 2015?
- What data is related in the visualization? What are the dimensions/variables?
- Approximately how many data points are recorded in the visualization?
- What makes this a good/bad visualization?
- What story is it conveying?
Data types

Tables
- Flat table
- Each row is an item
- Each column is an attribute
- Each cell is a value fully specified by the combination of row and column
- Multidimensional table
Networks

Trees

Fields

Geometry
- Shape of items with explicit spatial positions
- 0D
- 1D
- 2D
- 3D
- Maps
Attribute types

Semantics
- Type vs. semantic
- Key vs. value